Pricing Cryptocurrency Options With Volatility of Volatility

ABSTRACT We propose a novel option pricing model that explicitly incorporates volatility‐of‐volatility (VOV) dynamics and its associated risk premium. Our framework integrates realized variance and realized quarticity to capture latent VOV dynamics, addressing key challenges in cryptocurrency option pricing. Using Fourier inversion methods, we derive a closed‐form pricing formula for European‐style options. Empirical analysis with high‐frequency cryptocurrency option data shows that our model improves pricing accuracy, reducing implied volatility errors by 8.55% compared to benchmark models. The model outperforms benchmarks across all moneyness levels, remains robust for both short‐ and long‐maturity contracts, and maintains accuracy under high volatility. This study contributes to the literature by introducing a tractable and empirically validated approach to cryptocurrency option pricing through explicit VOV modeling.

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Publication Details

Journal
Journal of Futures Markets
Published
2025-08-17
DOI
https://doi.org/10.1002/fut.70029
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Pricing Cryptocurrency Options With Volatility of Volatility

Lingshan Du, Ji Shen
Journal of Futures Markets
Stochastic processes and financial applications
article

Pricing Cryptocurrency Options With Volatility of Volatility

Lingshan Du, Ji Shen
article en

Abstract

ABSTRACT We propose a novel option pricing model that explicitly incorporates volatility‐of‐volatility (VOV) dynamics and its associated risk premium. Our framework integrates realized variance and realized quarticity to capture latent VOV dynamics, addressing key challenges in cryptocurrency option pricing. Using Fourier inversion methods, we derive a closed‐form pricing formula for European‐style options. Empirical analysis with high‐frequency cryptocurrency option data shows that our model improves pricing accuracy, reducing implied volatility errors by 8.55% compared to benchmark models. The model outperforms benchmarks across all moneyness levels, remains robust for both short‐ and long‐maturity contracts, and maintains accuracy under high volatility. This study contributes to the literature by introducing a tractable and empirically validated approach to cryptocurrency option pricing through explicit VOV modeling.

Journal of Futures MarketsVol. 45(11)
Peking University (CN)
Openalex Percentile: Top 73%
Stochastic processes and financial applications
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Pricing Cryptocurrency Options With Volatility of Volatility — Lingshan Du, Ji Shen · Journal of Futures Markets (2025) | TGRS Research Map | TGRS